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A Natural Movement Database for Management, Documentation, Visualization, Mining and Modeling of Locomotion Experiments

  • Leslie M. Theunissen
  • Michael Hertrich
  • Cord Wiljes
  • Eduard Zell
  • Christian Behler
  • André F. Krause
  • Holger H. Bekemeier
  • Philipp Cimiano
  • Mario Botsch
  • Volker Dürr
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8608)

Abstract

In recent years, experimental data on natural, un-restrained locomotion of animals has strongly increased in complexity and quantity. This is due to novel motion-capture techniques, but also to the combination of several methods such as electromyography or force measurements. Since much of these data are of great value for the development, modeling and benchmarking of technical locomotion systems, suitable data management, documentation and visualization are essential. Here, we use an example of comparative kinematics of climbing insects to propose a data format that is equally suitable for scientific analysis and sharing through web repositories. Two data models are used: a relational model (SQL) for efficient data management and mining, and the Resource Description Framework (RDF), releasing data according to the Linked Data principles and connecting it to other datasets on the web. Finally, two visualization options are presented, using either a photo-realistic rendering or a plain but versatile cylinder-based 3D-model.

Keywords

Link Data Motion Capture Step Type Stick Insect Motion Capture Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Cruse, H., Dürr, V., Schilling, M., Schmitz, J.: Principles of insect locomotion. In: Arena, P., Patanè, L. (eds.) Spatial Temporal Patterns for Action-Oriented Perception in Roving Robots, pp. 43–96. Springer, Berlin (2009)CrossRefGoogle Scholar
  2. 2.
    Büschges, A.: Lessons for circuit function from large insects: towards understanding the neural basis of motor flexibility. Curr. Opin. Neurobiol. 22, 602–608 (2012)CrossRefGoogle Scholar
  3. 3.
    Dürr, V., Schmitz, J., Cruse, H.: Behaviour-based modelling of hexapod locomotion: linking biology and technical application. Arthr. Struct. Dev. 33, 237–250 (2004)CrossRefGoogle Scholar
  4. 4.
    Schmitz, J., Schneider, A., Schilling, M., Cruse, H.: No need for a body model: Positive velocity feedback for the control of an 18-DOF robot walker. Applied Bionics and Biomechanics 5, 135–147 (2008)CrossRefGoogle Scholar
  5. 5.
    Schneider, A., Paskarbeit, J., Schäffersmann, M., Schmitz, J.: Biomechatronics for embodied intelligence of an insectoid robot. In: Jeschke, S., Liu, H., Schilberg, D. (eds.) ICIRA 2011, Part II. LNCS, vol. 7102, pp. 1–11. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  6. 6.
    Safonova, A., Hodgins, J.K., Pollard, N.S.: Synthesizing physically realistic human motion in low-dimensional, behavior-specific spaces. ACM Transactions on Graphics 23, 514–521 (2004)CrossRefGoogle Scholar
  7. 7.
    Barbic, J., Safonova, A., Pan, J.-Y., Faloutsos, C., Hodgins, J.K., Pollard, N.S.: Segmenting motion capture data into distinct behaviors. In: Proc. Graphics Interface, GI 2004, pp. 185–194 (2004)Google Scholar
  8. 8.
    Parks, D.H.: Analyzing the structure of a motion capture database under a similarity metric. Technical Report CPSC533C: University of British Columbia. Vancouver, Canada (2008)Google Scholar
  9. 9.
    Müller, M., Röder, T., Clausen, M.: Efficient content-based retrieval of motion capture data. ACM Transactions on Graphics 24(3), 677–685 (2005)CrossRefGoogle Scholar
  10. 10.
    Demuth, B., Röder, T., Müller, M., Eberhardt, B.: An information retrieval system for motion capture data. In: Lalmas, M., MacFarlane, A., Rüger, S.M., Tombros, A., Tsikrika, T., Yavlinsky, A. (eds.) ECIR 2006. LNCS, vol. 3936, pp. 373–384. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  11. 11.
    Müller, M., Baak, A., Seidel, H.-P.: Efficient and robust annotation of motion capture data. In: Proc. ACM SIGGRAPH/Eurographics Symposium on Computer Animation. (2009)Google Scholar
  12. 12.
    Theunissen, L.M., Dürr, V.: Insects use two distinct classes of steps during unrestrained locomotion. PLOS one 8, e85321 (2013)Google Scholar
  13. 13.
    Cruse, H.: The control of the anterior extreme position of the hindleg of a walking insect. Carausius morosus. Physiol. Entomol. 4, 121–124 (1979)CrossRefGoogle Scholar
  14. 14.
    Lorensen, W.E., Cline, H.E.: Marching Cubes: A high resolution 3D surface construction algorithm. In: Proc. ACM SIGGRAPH, pp. 163–170 (1987)Google Scholar
  15. 15.
    Botsch, M., Kobbelt, L., Pauly, M., Alliez, P., Levy, B.: Polygon Mesh Processing. AK Peters (2010)Google Scholar
  16. 16.
    Kavan, L., Collins, S., Zara, J., O’Sullican, C.: Geometric skinning with approximate dual quaternion blending. ACM Transactions on Graphics 27(4) (2008)Google Scholar
  17. 17.
    Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web: a new form of Web content that is meaningful to computers will unleash a revolution of new possibilities. Sci. Am. 284, 34–43 (2001)CrossRefGoogle Scholar
  18. 18.
    Heath, T., Bizer, C.: Linked Data: Evolving the web into a global data space. Synthesis Lectures on the Semantic Web: Theory and Technology Morgan & Claypool (2011)Google Scholar
  19. 19.
    Wiljes, C., Cimiano, P.: Linked Data for the natural sciences: Two use cases in chemistry and biology. In: Proc. Workshop on the Semantic Publishing, SePublica 2012, pp. 48–59 (2012)Google Scholar
  20. 20.
    Schleif, F.-M., Mokbel, B., Gisbrecht, A., Theunissen, L., Dürr, V., Hammer, B.: Learning relevant time points for time-series data in the life sciences. In: Villa, A.E., Duch, W., Érdi, P., Masulli, F., Palm, G. (eds.) ICANN 2012, Part II. LNCS, vol. 7553, pp. 531–539. Springer, Heidelberg (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Leslie M. Theunissen
    • 1
    • 4
  • Michael Hertrich
    • 1
  • Cord Wiljes
    • 2
    • 4
  • Eduard Zell
    • 3
    • 4
  • Christian Behler
    • 3
  • André F. Krause
    • 1
    • 4
  • Holger H. Bekemeier
    • 1
  • Philipp Cimiano
    • 2
    • 4
  • Mario Botsch
    • 3
    • 4
  • Volker Dürr
    • 1
    • 4
  1. 1.Biological CyberneticsBielefeld UniversityGermany
  2. 2.Semantic ComputingBielefeld UniversityGermany
  3. 3.Computer GraphicsBielefeld UniversityGermany
  4. 4.Cognitive Interaction Technology, Center of Excellence (CITEC)Bielefeld UniversityGermany

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